Metal-polluted White Dwarfs with 21 <i>μ</i>m IR Excesses from JWST/MIRI: Planets or Dust?
Bibliographic record
Abstract
Abstract White dwarfs with metal pollution are caused by the accretion of rocky dust from tidally disrupted minor bodies and are signposts for planetary systems. These minor bodies are perturbed by planets that have survived post-main-sequence evolution. Open questions exist as to the typical mass of the perturbers and the specific planetary architectures that cause metal pollution. JWST’s sensitivity in the mid-IR has opened new doors to deciphering polluted white dwarfs. We present JWST Cycle 1 mid-infrared instrument imaging of four nearby metal-polluted white dwarfs with the goal of detecting and characterizing planetary companions. With deep mid-IR imaging we are sensitive to cold Jupiter-mass planet analogs. In addition to finding two candidate planetary companions, for the first time we detect significant excesses above the expected photospheric emission at 21 μm for two of our targets, WD 2149+021 and WD 2105−820. WD 2105−820 has a candidate planetary companion at a projected separation of 34 au and an IR excess—if both candidates are confirmed, it would represent the first WD multiplanet system. We investigate whether these excesses could be caused by very low luminosity warm dust disks or planets. While both are likely, we argue that the most likely explanation for the excesses is that they are the thermal emission from Jovian-mass planets in orbits with semimajor axes <10 au, using a combination of observational constraints. If most of the candidate planets presented here are confirmed, it would suggest that metal-polluted white dwarfs are frequently orbited by at least one giant planet.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".